Research ArticleWork Intensity, Low-Grade Inflammation, and Oxidative Status: AComparison between Office and Slaughterhouse Workers
Sieglinde Zelzer ,1 Franz Tatzber,2 Markus Herrmann,1 Willibald Wonisch ,3
Stefan Rinnerhofer,4 Michael Kundi,5 Barbara Obermayer-Pietsch,6 Tobias Niedrist,1
Gerhard Cvirn,3 Georg Wultsch,7 and Harald Mangge1
1Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Auenbruggerplatz 29,8036 Graz, Austria2Center of Molecular Medicine, Institute of Pathophysiology and Immunology, Medical University of Graz, Heinrichstrasse 31a,8010 Graz, Austria3Institute of Physiological Chemistry, Center for Physiological Medicine, Medical University of Graz, Stiftingtalstrasse 6 M1/D/3,8036 Graz, Austria4Exercise Physiology, Training and Training Therapy Research Group, Institute of Sports Science, University of Graz, Mozartgasse 14,8010 Graz, Austria5Department of Environmental Health, Center for Public Health, Medical University Vienna, Kinderspitalgasse 15,1090 Vienna, Austria6Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Auenbruggerplatz 15,8036 Graz, Austria7Arbeitsmedizinisches Institut, Graz, Herrgottwiesgasse 149, 8055 Graz, Austria
Correspondence should be addressed to Sieglinde Zelzer; [email protected]
Received 15 December 2017; Accepted 11 March 2018; Published 18 April 2018
Limited knowledge exists about the impact of physical workload on oxidative stress in different occupational categories. Thus, weaimed to investigate the oxidative and inflammatory status in employees with different physical workloads. We enrolled a total of79 male subjects, 27 office workers (mean age 38.8± 9.1 years) and 52 heavy workers, in a slaughterhouse (mean age 40.8± 8.2years). Fasting blood was drawn from an antecubital vein in the morning of the midweek before an 8-hour or 12-hour work shift.The antioxidative capacity was assessed measuring total antioxidant capacity (TAC), uric acid, total polyphenols (PPm), andendogenous peroxidase activity (EPA). Total peroxides (TOC), malondialdehyde (MDA), and myeloperoxidase (MPO) wereanalyzed as prooxidative biomarkers, and an oxidative stress index (OSI) was calculated. In addition, hsCRP, interleukin-6(IL-6), MDA-LDL IgM antibodies, galectin-3, adrenocorticotropic hormone (ACTH), and the brain-derived neurotrophicfactor (BDNF) were measured as biomarkers of chronic systemic inflammation and emotional stress. TOC (p = 0 032),TAC (p < 0 001), ACTH (p < 0 001), OSI (p = 0 011), and hsCRP (p = 0 019) were significantly increased in the heavyworkers group, while EPA, BDNF (p < 0 001), and polyphenols (p = 0 004) were significantly higher in office workers.Comparison between 8 and 12 h shifts showed a worse psychological condition in heavy workers with increased levels forhsCRP (p = 0 001) and reduced concentration of BDNF (p = 0 012) compared to office workers. Oxidative stress andinflammation are induced in heavy workers and are particularly pronounced during long working hours, that is, 12-hour versus8-hour shifts.
HindawiOxidative Medicine and Cellular LongevityVolume 2018, Article ID 2737563, 7 pageshttps://doi.org/10.1155/2018/2737563
Modern life-style, that is, physical inactivity and fast food aswell as occupational and environmental conditions, mayinduce oxidative stress. Different types of stress can be dis-tinguished at the cellular and tissue level—namely, photoox-idative stress, drug-dependent oxidative stress, metabolicoxidative stress, environmental oxidative stress, and nitrosa-tive stress [1].
Reactive oxygen species (ROS) are endogenously gener-ated, among others, in the respiratory chain. Hence, meta-bolic activity increases ROS production. These species reactwith biological molecules like lipids, carbohydrates, proteins,and even DNA, which are associated with the pathogenesis ofdegenerative diseases. Oxidative stress (OS) is associated withchronic inflammation, with a potential impact on diabetesmellitus, atherosclerosis, and cardiovascular and neurodegen-erative diseases [2–5]. An increased consumption of oxygenduring physical exercise also increases ROS production lead-ing to oxidative stress and lipid peroxidation in athletes [6–8].Nevertheless, increased ROS production during sports is alsobeneficial because it stimulates the antioxidative system [9].Moreover, OS is a key factor during aging [10] together withother factors like deregulated autophagy, mitochondrial dys-function, and telomere shortening [11]. Besides its involve-ment in the physiologic process of aging, OS appears to playan important role in the pathophysiology of several occupa-tional diseases [12, 13]. Common problems in night and shiftworkers, such as fatigue, sleep problems, anxiety, difficultiesinmaintaining regular life-styles, and reduced recovery times,represent an increased health risk due to physiologicalexhaustion and a decreased capacity for regulation [14].
Nevertheless, there is limited knowledge about theimpact of physical workload on OS in different occupationalgroups. Heavy workers often suffer from excessive workloadand lack of social support. Shift work with extended workinghours might negatively affect the psychological status ofemployees and reduce their motivation. It can be hypothe-sized that high physical and emotional stress in heavyworkers is associated with increased OS and inflammation.
The present study aimed at comparing the oxidative andinflammatory status between office workers and heavyworkers with a particular focus on the biochemical effect ofextended working hours (8- to 12-hour shifts).
2. Materials and Methods
2.1. Study Population. We enrolled 79 healthy male volun-teers between 18 and 65 years at their workplace. Thereof,27 employees were office workers (age 38.8± 9.1 years) and52 heavy workers in a slaughterhouse (age 40.8± 8.2 years).Exclusion criteria were infections, for example, flu-like infec-tion, chronic diseases, and certified reduced work capacitydue to illness. The study was approved by the ethics commit-tee of the Medical University of Graz (EK number 26-488 ex13/14) and conducted in compliance with guidelines forhuman studies as described in the Helsinki Declaration of1975, revised in 1996. Written inform consent was obtainedfrom all study participants.
2.2. Laboratory Analysis
2.2.1. Blood Sampling. Blood was drawn from an antecubitalvein between 6:00 a.m. and 6:30 a.m., before an 8-hour workshift from 79 workers (27 office and 52 heavy workers). In asubgroup of 26 office workers and 8 heavy workers, we inves-tigated the effects of twelve hours of work. Blood samplingwas performed in the midweek, Wednesdays or Thursdays.Samples were immediately transferred on ice to the Labwithin two hours, centrifuged, and stored at −80°C until use(6 to 13 months).
2.2.2. Inflammatory Parameters. High-sensitivity C-reactiveprotein (hsCRP) and interleukin 6 (IL-6) were determinedon a COBAS® 8000 analyzer with turbidimetric and electro-chemiluminescence immunoassays (ECLIA), respectively,from Roche Diagnostics (Rotkreuz, Switzerland). All mea-surements were batched into a single run. The total impreci-sion of both assays were below 5%. Galectin-3 was measuredusing the Human Galectin-3 Quantikine ELISA Kit fromR&D (Minneapolis, USA).
2.2.3. Oxidative Stress Biomarkers. Malondialdehyde (MDA)was determined by GC-MS from Thermo Fisher Scientific(CA, USA). After addition of MDA-d 2 as internal standard,derivatizationwith 2,4-dinitrophenylhydrazine, and chemicalionization in negative mode, the representative ions m/z 204(for MDA) andm/z 206 (for MDA-d 2) were recorded [15].
Colorimetricmethodswere used to determine total perox-ides (TOC), endogenous peroxidase activity (EPA), and thetotal antioxidant capacity (TAC) purchased fromLDN (LaborDiagnostika Nord, Nordhorn, Germany). These assays arebased on the reaction between hydrogen peroxide, horserad-ish peroxidase, and tetramethylbenzidine to give a blue-green colour. After the addition of the stop solution, thecolour changes to yellow, which can be measured at 450nm(reference wavelength 620nm). A linear standard curve wasused for quantification. The intra- and interassay coefficientsof variance were less than 5% for all assays [16]. MDA-LDLIgM was measured with the MDA-LDL-IgM ELISA fromOmnignostica Ltd. (Höflein/D., Austria), which is standard-ized on a human monoclonal antibody as described previ-ously [17]. Serum myeloperoxidase (MPO) concentrationswere measured with the MPO enzyme-linked immunosor-bent assay (ELISA) Kit (Immundiagnostik AG, Bensheim,Germany) according to the manufacturer’s instructions.The total imprecision of both ELISA assays was below 7%.Uric acid was determined with the enzymatic colorimetrictest from Roche on a COBAS 8000 analyzer.
In the case of the brain-derived neurotrophic factor(BDNF), we used the Quantikine human BDNF immunoas-say from R&D systems (Minneapolis, USA). Adrenocortico-tropic hormone (ACTH) was determined with the ACTHELISA from Hölzel Diagnostica (Köln, Germany), and totalpolyphenols (PPm) were determined according to the manu-facturer’s instructions with an adapted Folin-Ciocalteumicrotitre method from Omnignostica Ltd. (Höflein/D.,Austria). In short, the principle of this method is based onthe reaction of polyphenols with transition metals. This leads
2 Oxidative Medicine and Cellular Longevity
to a dark-coloured complex, which can be measured at766nm. Samples are quantified by the use of a standard curvewith serial dilutions of a polyphenol standard. The intra- andinterassay coefficients of variance were less than 5%.
2.3. Statistical Analysis. Statistical analyses were carried outusing SPSS 23.0 for Windows 10 (IBM Corp., USA) and Stata12 (StataCorp, TX, USA). Comparisons between groups weredone by the use of the general linear model including bodymass index (BMI) as a covariate because heavy workers hadsignificantly higher BMI which itself could be related to oxi-dative stress and inflammation, as reported previously [18].Residuals of analyses were stored and tested for deviationsfrom a normal distribution by Kolmogorov-Smirnov testswith Lilliefors-corrected p values. In case of a significantdeviation, distribution of residuals was inspected, and in caseof a skewed distribution, a logarithmic transformation wasapplied. In all such cases, normality of residuals was obtainedafter transformation. Homogeneity of variance was tested byLevene’s tests. Data are summarized as means within groupsand 95% confidence intervals (back-transformed if necessaryto the original scale). A similar approach was applied forcomparison of 8 h versus 12 h shifts. In this case, thewithin-subject factor (8 h/12 h shift length) and between-subject factor groups (office versus heavy workers) and theirinteraction were tested by analysis of variance. Comparisonsof 8 h and 12 h shifts within groups were done by linearcontrasts. Variables were log-transformed in accordance withthe analysis of baseline data. Based on the ratio between ROSand serum antioxidant capacity, the oxidative stress index(OSI) was calculated using the formula TOC mmol/L /TA
C mmol/L × 100 . For all statistical tests, p < 0 05 was con-sidered significant.
3. Results
An overview about the anthropometric data of the studycohort is given in Table 1. Due to the fact that the BMI wassignificantly increased in heavy workers versus officeworkers, all further analyses were corrected with respect tothis biometric parameter, because BMI itself was shown tobe associated with OS [18].
Heavy workers had significantly increased TAC (p <0 001), TOC (p = 0 032), hsCRP (p = 0 019), and ACTH(p < 0 001) (for details, see Figures 1 and 2 and Table 1)and OSI levels (p = 0 011; Table 1). In contrast, EPA (p <0 001), polyphenols (p = 0 004), and BDNF (p < 0 001) levelswere significantly higher in office workers (Figures 3 and 4).Uric acid, MDA, MPO, IL-6, MDA-LDL IgM, and galectin-3 did not differ between the groups (Table 1).
Comparison between 8-hour and 12-hour shifts revealedsignificant differences exclusively after a 12-hour shift inheavy workers, that is, a significant increased ACTH level(p = 0 001), while BDNF was significantly decreased at over-time work (p = 0 012) (Table 2). Correlation analysisbetween oxidative stress biomarkers revealed a significantnegative correlation between TAC and EPA in both workinggroups whereas a positive correlation was found for TACand uric acid (Table 3). TOC correlated positively withhsCRP in both working groups (r = 0 612 and 0.493 in officeand heavy workers, resp.). In contrast, IL-6 was correlatedto TOC merely in office workers (r = 0 462), while the
Table 1: Baseline characteristics of study participants and results of measurements after an 8-hour work shift.
Office workers (n = 27) Heavy workers (n = 52)Mean (95% confidence interval) p
Age, yrs 38.2 (35.2–41.1) 40.8 (38.5–43.0) 0.175
Body mass index, kg/m2 26.1 (24.5–27.6) 28.3 (27.1–29.5) 0.026
BDNF, pg/mL 22880 (16051–32616) 7417 (5651–9735) <0.001p values from the general linear model with body mass index included as covariate. hsCRP = high-sensitivity C-reactive protein; IL-6 = interleukin-6;OSI = oxidative stress index; ACTH= adrenocorticotropic hormone; ST2 = suppression of tumorigenicity 2; BDNF = brain-derived neurotrophic factor.
3Oxidative Medicine and Cellular Longevity
correlation with polyphenols was only significant in heavyworkers (r = 0 565). Furthermore, TAC showed a highlysignificant negative correlation with TOC in office workers(r = −0 526) (Table 3).
4. Discussion
In the present study, we indicated an increased inflamma-tion through raised hsCRP levels at baseline in heavyworkers compared to office workers. This was associatedwith oxidative stress, that is, increased total peroxides anda concomitant decrease of peroxidase activity. In addition,we observed a decrease in polyphenols, although the totalantioxidant capacity was increased (Table 1). OSI, whichreflects the redox balance between prooxidants and antioxi-dants, showed significant differences between these twoworking groups.
This was further related to psychological stress, due to anincrease in ACTH and a very low level of BDNF indicatingemotional stress (Table 1). In spite of significant differences
in several biomarkers between office workers and heavyworkers in a slaughterhouse, it must be emphasized that thismight even be an underestimation due to the working envi-ronment of the latter; that is, low temperatures were previ-ously associated with reduced OS [19, 20].
A stressful working environment may affect the healthof employees. Night shifts disrupt the circadian rhythmand increase OS [21]. There can be no doubt that a betterunderstanding of the main stressors in the workplace wouldbe effective in preventing disease and that determination ofoxidative stress biomarkers could be helpful in this context[7]. Since reduction of sickness-related absenteeism implieseconomic benefits, individual health care at the workplaceshould be given priority. Increased disease risks in workerswith demanding jobs have frequently been reported, amongothers by Ramey et al. [22]. Release of catecholamines andincreased blood pressure, along with chronic work-relatedstress, may lead to cardiovascular diseases. A combinationof psychological and physical stress could induce chronicinflammation and subsequent disease [23]. For such reasons,a dietary regimen including antioxidants was suggested
10
9
8
7
6
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4
3
hsCR
P (m
g/L)
2
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0Office workers Heavy workers
p = 0.019
Figure 2: Box plots (medians, interquartile, and nonoutlier ranges)of hsCRP by groups of workers.
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14
12
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8
6
4
2
00Office workers Heavy workers
p < 0.001
EPA
(U/L
)
Figure 3: Box plots (medians, interquartile, and nonoutlier ranges)of endogenous peroxidase activity by groups of workers.
45000
40000
35000
30000
25000
20000
15000
10000
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0Office workers Heavyworkers
BDN
F (p
g/m
L)p < 0.001
Figure 4: Box plots (medians, interquartile, and nonoutlier ranges)of brain-derived neurotrophic factor by groups of workers.
Figure 1: Box plots (medians, interquartile, and nonoutlier ranges)of total oxidant capacity by groups of workers.
4 Oxidative Medicine and Cellular Longevity
[24, 25], but it is not clear if such a strategy is of muchhelp [26], especially if the working conditions otherwiseremain unchanged.
Notably, sensitive biomarkers identified these effects,pointing to early development of an imbalance in the redoxsystem. Nevertheless, there were no changes in MDA, oneof the end products of lipid peroxidation, MDA-LDL IgM,a biomarker for immune activation, MPO, uric acid, andgalectin-3. Although the significant differences seen betweenoccupational groups were fluctuations within “normal”ranges, it must be kept in mind that individuals may beexposed to these changes throughout their working lives.Such mild chronic stress responses over prolonged timeperiods are in line with our results and were also reportedin an animal experiment with increased oxidative stress and
consumption of antioxidants, especially in the pancreas. Thisled to systemic inflammation and contributed to degenera-tive diseases [27].
It was striking that overtime was accompanied by analmost threefold increase of ACTH and a significant decreasein BDNF in laborers only (Table 2), pointing to a combinedimpact of a heavy workload and 12 h shift.
Overtime, shift work [23] and extended exposure tooccupational and environmental stressors diminish antioxi-dative capacity, which may elevate the impact of increasedproduction of OS due to a heavy workload [28, 29]. Walkeret al. [30] reported that inflammation and alterations of theimmune system were associated with altered mood andreduced well-being, thus highlighting the need for improvedrisk management in the workplace.
Table 2: Comparison of stress and inflammatory biomarkers between 8 and 12 h shifts in office and heavy workers.
We observed a significant correlation between the totalantioxidant capacity and uric acid, as has been reported pre-viously [18]. There is also a strong inverse correlationbetween endogenous peroxidase activity and total antioxi-dant capacity. The correlation between (hsCRP) and oxida-tive stress (TOC) underlines the link between inflammationand cellular stress responses (Table 3).
Monitoring with sensitive biomarkers may be advisable,particularly in cases of smoking, obesity, and older age, tocounteract an accumulation of stress-related biologicalchanges that couldhave adversehealth effects. Researchofoxi-dative stress under real-life working conditions is a win-winsituation for both employers and employees. It could help totailorhealth care andcounseling forworkers,minimizing sick-ness absenteeism and reducing fluctuation in the workforce.
The small number of manual laborers doing a 12-hourwork shift could be a limitation for this study due to insuffi-cient compliance. In addition, the lack of female subjects is aconstraint of this work. Therefore, further research in theseworking groups with a larger collective, including femaleworkers, should be performed.
In conclusion, we found increased oxidative stress andinflammation in manual laborers as compared to officeworkers. Indications of psychological stress were observedfor overtime work in combination with hard physical work.The relationship between antioxidant consumption, oxida-tive stress, and inflammation was clearly shown in the corre-lation analysis. These data provide a solid basis for furtherresearch on this important subject with a larger collective.
Abbreviations
ROS: Reactive oxygen speciesOS: Oxidative stressOSI: Oxidative stress indexTAC: Total antioxidant capacityTOC: Total oxidant capacityEPA: Endogenous peroxidase activityMDA: MalondialdehydeMPO: MyeloperoxidasePPm: Total polyphenolsACTH: Adrenocorticotropic hormonehsCRP: High-sensitivity c-reactive proteinIL-6: Interleukin-6BDNF: Brain-derived neurotrophic factorSD: Standard deviationIQR: Interquartile range95% CI: 95% confidence intervalIQRs: Interquartile rangesCV: Coefficient of variationICC: Intraclass correlation coefficientBMI: Body mass index.
Conflicts of Interest
The authors declare they have no competing interests thatmight be perceived to influence the results and discussionreported in this article—except W. Wonisch, who is a mem-ber of Omnignostica Ltd.
Authors’ Contributions
Sieglinde Zelzer and Franz Tatzber contributed equally tothis study.
Acknowledgments
The authors gratefully acknowledge the scientific advice andsupport of G. Reibnegger and S. Holasek. Language editingwas done by Eugenia Lamont. This work is dedicated to mydaughter Marion Zelzer (S. Z.)
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